108 research outputs found
Volatility forecasting in the Chinese commodity futures market with intraday data
Given the unique institutional regulations in the Chinese commodity futures market as well as the characteristics of the data it generates, we utilize contracts with three months to delivery, the most liquid contract series, to systematically explore volatility forecasting for aluminum, copper, fuel oil, and sugar at the daily and three intraday sampling frequencies. We adopt popular volatility models in the literature and assess the forecasts obtained via these models against alternative proxies for the true volatility. Our results suggest that the long memory property is an essential feature in the commodity futures volatility dynamics and that the ARFIMA model consistently produces the best forecasts or forecasts not inferior to the best in statistical terms
Transaction Costs, Liquidity and Expected Returns at the Berlin Stock Exchange, 1892-1913
Oil, the Baltic Dry index, market (il)liquidity and business cycles:evidence from net oil-exporting/oil-importing countries
Forecasting Bond Risk Premia Using Technical Analysis
This paper is selected as one of the Top Ten Paper in Forecasting in SSRN
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